The theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five chapters cover the basics of probability and both discrete and continuous random variables. The later chapters have a more specialized coverage, including random vectors, Gaussian random vectors, random processes, Markov Chains, and convergence. Describing tools and results that are used extensively in the field, this is more than a textbook; it is also a reference for researchers working in communications, signal processing, and computer network traffic analysis. With over 300 worked examples, some 800 homework problems, and sections for exam preparation, this is an essential companion for advanced undergraduate and graduate students. Further resources for this title, including solutions (for Instructors only), are available online at www.cambridge.org/9780521864701.
Recent study shows that the existing first order canonical timing model is not sufficient to represent the dependency of the gate delay on the variation sources when processing and operational variations become more and more significant. Due to the nonlinearity of the mapping from variation sources to the gate/wire delay, the distribution of the delay is no longer Gaussian even if the variation sources are normally distributed.A novel quadratic timing model is proposed to capture the non-linearity of the dependency of gate/wire delays and arrival times on the variation sources. Systematic methodology is also developed to evaluate the correlation and distribution of the quadratic timing model. Based on these, a novel statistical timing analysis algorithm is propose which retains the complete correlation information during timing analysis and has the same computation complexity as the algorithm based on the canonical timing model.Tested on the ISCAS circuits, the proposed algorithm shows 10× accuracy improvement over the existing first order algorithm while no significant extra runtime is needed.
An algorithm is developed for the design of a nonlinear, n-sensor, distriboted estimation system sobject to communication and computation mnstraints. Tbe algorithm uses only bivariate pmbabiIity dlstrbntio~~ and ykMs l d y optimal esthnstora that s a w the RQpind system constraints. It is ssorsl that fhe d g o r i h~ is a generalizstioe of the elpssicpl Lloyd-Max results. I& ~nns-Nonlineat estimation, dismted estimation, sensor fodon, Uyd-Max algorithm. I. INTRODUCTION Consider the distributed estimation system shown in Fig. 1. The system consists of n sensor platforms whose respective measurements, Y1 ,. .-, Y,, are related to some unobservable quantity, say Manwaipt received August 10, 1992, revised December 15, 1992. This work was supported in part by the Air Force Office of Scientific Research under Grant AFOSR-90-0181. This work was presented in part at the 1990
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